LOGGER.info(self.initialLoggingString, metricName)
# Get path to data
knownDataFilePath = self._getPathToData(knownDataFile)
# Load and send data
sock = self._getSocketConnection()
LOGGER.info("Sending data from %s ...", knownDataFile)
labels = self._loadAndSendData(sock, knownDataFilePath, metricName)
# Make sure the metric was properly created and wait for the expected
# records to be stored. NOTE: Waiting for all records to be stored
# facilitates constistent stats calculation in Grok, resulting in
# consistency of results from one run of the test to the next.
uid = self.checkMetricCreated(metricName, numRecords=len(labels))
# Save the uid for later
LOGGER.info("Metric %s has uid: %s", metricName, uid)
# Send model creation request
self._createModel(uid)
return self._verifyResults(uid, metricName, knownDataFilePath, labels,
expectedResults)
if __name__ == "__main__":
unittest.main()
modelId = adapter.importModel(spec)
newModelSpec = dict(modelSpec)
with self.engine.connect() as conn:
repository.getMetric(conn, modelId)
autostack = repository.getAutostackFromMetric(conn, modelId)
self.addCleanup(self._deleteAutostack, autostack.uid)
newModelSpec["metricSpec"]["autostackId"] = autostack.uid
self.validateModel(modelId, modelSpec, autostack)
def validateModel(self, modelId, modelSpec, autostack):
self.assertIsNotNone(modelId)
with self.engine.connect() as conn:
metricObj = repository.getMetric(
conn,
modelId,
fields=[schema.metric.c.status, schema.metric.c.parameters])
self.assertIn(metricObj.status,
[MetricStatus.CREATE_PENDING, MetricStatus.ACTIVE])
self.assertEqual(json.loads(metricObj.parameters), modelSpec)
self.assertEqual(
repository.getAutostackFromMetric(conn, modelId).uid,
autostack.uid)
if __name__ == "__main__":
unittest.main()